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DeepSeek vs Moonshot AI
Two Chinese open-weight labs at different price points. DeepSeek is the cheap, permissive MIT option; Moonshot's Kimi K3 is the more capable model at $3 in and $15 out.
By The Subconscious Team · Updated
DeepSeek vs Moonshot AI: key differences
DeepSeek and Moonshot AI both release open weights and sell hosted APIs with 1M context, but they sit at opposite ends of the price scale. DeepSeek's main model, V4.1 Flash, is $0.30 in and $1.20 out at peak with image understanding, and every off-peak hour is half that. Moonshot's Kimi K3 costs $3 in and $15 out, with cached input at $0.30. For that premium, K3 scored 93.4% on SWE-bench Verified with Vals AI, fourth overall behind three closed models, and Artificial Analysis placed it third on its Intelligence Index.
Licensing and speed also separate them. DeepSeek's weights are MIT-licensed, while K3's custom license adds a commercial agreement above $20M in hosting revenue and a branding clause at large scale, and self-hosting it takes a 64+ accelerator cluster. K3 always thinks and runs around 33 tokens per second. DeepSeek gives low, high and max reasoning effort settings to control output tokens. Hard repo-scale coding favors K3. Cost-sensitive agents and batch work, especially in off-peak windows, favor DeepSeek. Both host their first-party APIs from China-based labs, so enterprise data rules apply to each.
What DeepSeek and Moonshot AI do
DeepSeek
DeepSeek is the Chinese lab whose open-weight models reset price expectations for the whole market. Its main model is V4.1 Flash, with 1M context and 384K max output, which shipped September 10, 2026 with built-in image understanding at $0.30 in and $1.20 out at peak. An updated checkpoint, V4.1-Flash-1017, replaced it on October 17 at the same price. DeepSeek had planned to route deepseek-v4-pro requests to V4.1 Flash from September 14 but reversed course, and still serves V4 Pro at $1.32 in and $3.96 out at peak until a V4.1 Pro launches. Cache hits cost a few cents per million or less, and the weights ship on Hugging Face under an MIT license.
Example models: DeepSeek V4.1 Flash
Full DeepSeek profileMoonshot AI
Moonshot AI is the Beijing lab behind the Kimi models. Its flagship Kimi K3 launched July 16, 2026 as a 2.8 trillion parameter mixture-of-experts model that activates 16 of 896 experts per token, with native vision and a 1M token context. It is the first open model in the 3T class, and full weights landed on Hugging Face on July 27. The hosted API costs $3 in and $15 out per million tokens, with cached input at $0.30, and it runs through an OpenAI compatible endpoint, Kimi Code in the terminal, OpenRouter and Cloudflare Workers AI.
Example models: Kimi K3.1 Pro, Kimi K3
Full Moonshot AI profileShould you choose DeepSeek or Moonshot AI?
DeepSeek
Choose DeepSeek for
- Cost-sensitive agents that can shift work into off-peak hours
- Self-hosting under a plain MIT license
- Controlling output tokens with reasoning effort settings
Moonshot AI
Choose Moonshot AI for
- Hard, repo-scale coding where benchmark scores justify higher prices
- Document-heavy and visual agent work on a 1M window
- Teams that want top-tier open-weight coding quality
DeepSeek vs Moonshot AI at a glance
| Attribute | DeepSeek | Moonshot AI |
|---|---|---|
| Model access | Open weights (MIT) | Open weights, custom license |
| Flagship models | DeepSeek V4.1 Flash | Kimi K3.1 Pro, Kimi K3 |
| Speed | ~209 tok/s on V4.1 Flash | ~33 tok/s on Kimi K3 |
| Price | Off-peak hours at half price | $2 in, $10 out (K3.1 Pro); $3 in, $15 out (K3) |
| Customization | Open weights to fine-tune | Open weights to fine-tune |
| Deployment | First-party API, Hugging Face weights | API, Kimi Code, OpenRouter |
| Long context | 1M, 384K max output | 1M |
Frequently asked questions
What is the difference between DeepSeek and Moonshot AI?
Two Chinese open-weight labs at different price points. DeepSeek is the cheap, permissive MIT option; Moonshot's Kimi K3 is the more capable model at $3 in and $15 out.
When should I choose DeepSeek over Moonshot AI?
Cost-sensitive agents that can shift work into off-peak hours; Self-hosting under a plain MIT license; Controlling output tokens with reasoning effort settings.
When should I choose Moonshot AI over DeepSeek?
Hard, repo-scale coding where benchmark scores justify higher prices; Document-heavy and visual agent work on a 1M window; Teams that want top-tier open-weight coding quality.
Is DeepSeek or Moonshot AI cheaper?
DeepSeek: Off-peak hours at half price. Moonshot AI: $2 in, $10 out (K3.1 Pro); $3 in, $15 out (K3). The cheaper choice depends on the model and workload.
Which has more context, DeepSeek or Moonshot AI?
DeepSeek: 1M, 384K max output. Moonshot AI: 1M.
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